Technical Field
The present invention relates to object parsing, and more particularly to a surveillance system with landmark localization on objects in images using convolutional neural networks.
Description of the Related Art
Parsing 3D object geometry is a critical capability for occlusion reasoning and scene understanding. However, current approaches to parsing 3D object geometry suffer from many deficiencies including, but not limited to, the lack of joint optimization for 2D and 3D keypoints, partial view ambiguity, 3D prediction errors, applicability to only low resolution images, and so forth.
Thus, there is a need for an improved approach to landmark localization on objects in images, particularly with respect to surveillance systems.